DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments with respect to claims 1-31 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4-5, 13, 15, 18-19, 27-30 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al (US 2024/0232663) and further in view of Reinspach et al (US 11,694,682).
For claim 1, Smith et al teach a method for executing collaborative content creation in a computing environment, the method comprising:
receiving, by a content creation system, a first input from a first user and a second input from a second user (e.g. Fig 1A: “To the park please”, “Yes”, paragraph 89: “…The processor 204 may perform determining, via the machine learning model, to prompt the user for an additional utterance based on content included in a most recently-received utterance in 244D, determining the task comprises determining a task of the transport based on the utterance and the one or more additional utterances in 245D, determining to request the user to confirm content included in a previously-received utterance based on the machine learning model 246D, predicting an intent of the user after each utterance based on an aggregation of utterances during a conversation with the user and determining that enough information is available based on the aggregation of utterances in 247D…”),
analyzing, by an input fusion system (e.g. paragraph 89: “…predicting an intent of the user after each utterance based on an aggregation of utterances during a conversation with the user and determining that enough information is available based on the aggregation of utterances in 247D…”), the first input and the second input to determine a presence of prompt data by using a machine learning model (e.g. paragraph 89: “…predicting an intent of the user after each utterance based on an aggregation of utterances during a conversation with the user and determining that enough information is available based on the aggregation of utterances in 247D…”),
generating, by the action generation system, first action data based on the prompt data and the machine learning model (e.g. paragraph 89: “…predicting, via the machine learning model, a next action to be taken by the virtual assistant based on the received utterance associated and one or more previously-received utterances from the user which are associated with a same task in 249D…” ); and
executing, by the action generation system, a first action in the computing environment based on the first action data (e.g. paragraph 89: “…predicting, via the machine learning model, a next action to be taken by the virtual assistant based on the received utterance associated and one or more previously-received utterances from the user which are associated with a same task in 249D…” ).
Smith et al do not further disclose second user device. Reinspach et al teach second user device (e.g. figure 1A: “Alex, add ACME detergent to Cart” so the first user device is Alex 104, Figure 1B: “Check out” second device is 108). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Reinspach et al into the teaching of Smither et al to have utilized smart device and digital assistant to improve convenience for user (e.g. column 1, lines 5-21, Reinspach et al ).
Claim 29 is rejected for the same reasons as discussed in claim 1 above.
Claims 15 and 28 are rejected for the same reasons as discussed in claim 1 above, wherein figure 7 shows processor 704.
For claims 4 and 18, Smith et al teach at least one of the first input or the second input comprises text data (e.g. paragraph 62: “text message” or paragraph 66: speech-to-text).
For claims 5 and19, Smith et al teach converting, by the input fusion system, at least one of the first input or the second input into converted data, wherein at least one of the first input or the second input comprises at least one of image data, audio data (e.g. paragraph 89: utterance), or haptic data, and wherein the converted data comprises converted text data (e.g. paragraph 66: speech-to-text).
For claims 13, 27 and 30, Smith et al teach the first input and the second input are received asynchronously (e.g. figure 1, “To the park please”, “yes”).
Claims 2-3, 6-7, 16-17 and 20-21 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al and Reinspach et al, as applied to claims 1, 4-5, 13, 15, 18-19, 27-30, and further in view of Gonsalves et al (US 2008/0010225).
For claims 2 and 16, Smith et al and Reinspach et al do not further disclose upon determining the presence of the duplicate data in at least one of the first input or the second input, removing, by the input fusion system, the duplicate data from at least one of the first input or the second input. Gonsalves et al teach upon determining the presence of the duplicate data in at least one of the first input or the second input, removing, by the input fusion system, the duplicate data from at least one of the first input or the second input (e.g. paragraph 63: The data is then "fused" and "normalized". The fusion process reduces (ideally removes) any redundancy in received data due to, for example, the same event or measurement being reported multiple times by different sensors. The fusion process also verifies the validity of received data. ) It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gonsalves et al into the teaching of Smith et al and Reinspach et al to fused the input data to remove any redundancy (e.g. paragrpah 63, Gonsalves et al) to improve the efficiency of the system.
For claims 3 and 17, Smith et al and Reinspach et al do not further disclose upon determining the presence of the duplicate data and the redundancy data in at least one of the first input or the second input, removing, by the input fusion system, the duplicate data and the redundancy data from at least one of the first input or the second input. Gonsalves et al teach upon determining the presence of the duplicate data and the redundancy data in at least one of the first input or the second input, removing, by the input fusion system, the duplicate data and the redundancy data from at least one of the first input or the second input. (e.g. paragraph 63: The data is then "fused" and "normalized". The fusion process reduces (ideally removes) any redundancy in received data due to, for example, the same event or measurement being reported multiple times by different sensors. The fusion process also verifies the validity of received data. ) It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gonsalves et al into the teaching of Smith et al and Reinspach et al to fused the input data to remove any redundancy (e.g. paragraph 63, Gonsalves et al) to improve the efficiency of the system.
For claims 6 and 20, Smith et al and Reinspach et al teach converted text data (speech-to-text). Smith et al do not further disclose upon determining the presence of the duplicate data or the redundancy data, removing, by the input fusion system, text data corresponding to at least one of the duplicate data or the redundancy data. Gonsalves et al teach upon determining the presence of the duplicate data or the redundancy data, removing, by the input fusion system, text data corresponding to at least one of the duplicate data or the redundancy data. (e.g. paragraph 63: The data is then "fused" and "normalized". The fusion process reduces (ideally removes) any redundancy in received data due to, for example, the same event or measurement being reported multiple times by different sensors. The fusion process also verifies the validity of received data. ) It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gonsalves et al into the teaching of Smith et al and Reinspach et al to fused the input data to remove any redundancy (e.g. paragraph 63, Gonsalves et al) to improve the efficiency of the system.
For claims 7 and 21, Smith et al teach a direct user input or an indirect user input (e.g. utterance or figure 1A: “To the Park Please”). Smith et al and Reinspach et al do not further disclose the machine learning model facilitates determining the presence of the duplicate data, the redundancy data, and/or the prompt data. Gonsalves et al teach the machine learning model facilitates determining the presence of the duplicate data, the redundancy data, and/or the prompt data (e.g. paragraph 63: The data is then "fused" and "normalized". The fusion process reduces (ideally removes) any redundancy in received data due to, for example, the same event or measurement being reported multiple times by different sensors. The fusion process also verifies the validity of received data. ) It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Gonsalves et al into the teaching of Smith et al and Reinspach et al to fused the input data to remove any redundancy (e.g. paragraph 63, Gonsalves et al) to improve the efficiency of the system.
Claims 8-11, 22-25 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al and Reinspach et al, as applied to claims 1, 4-5, 13, 15, 18-19, 27-30, and further in view of Baughman et al (US 9,891,884).
For claims 8 and 22, Smith et al and Reinspach et al do not further disclose the computing environment is a virtual environment. Baughman et al teach the computing environment is a virtual environment (e.g. column 2, line 65-column 3, lines 15: One approach by which a user may change the context is through the application of sound modification or augmentation in response to object recognition and/or sound detection associated with a particular user response, determined by machine learning). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Baughman et al into the teaching of Smith et al and Reinspach et al to improve user experience (e.g. Baughman et al, column 2, line 65-coolumn 3, line 15).
For claims 10 and 24, Smith et al and Reinspach et al do not further disclose the first action is creating or modifying an element in a space of the virtual environment. Baughman et al teach the first action is creating or modifying an element in a space of the virtual environment. (e.g. column 2, line 65-column 3, lines 15: One approach by which a user may change the context is through the application of sound modification or augmentation in response to object recognition and/or sound detection associated with a particular user response, determined by machine learning). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Baughman et al into the teaching of Smith et al and Reinspach et al to improve user experience (e.g. Baughman et al, column 2, line 65-coolumn 3, line 15).
For claims 11 and 25, Smith et al and Reinspach et al do not further teach the element is at least one of a visual element or an audio element. Baughman et al teach the element is at least one of a visual element or an audio element. (e.g. column 2, line 65-column 3, lines 15: One approach by which a user may change the context is through the application of sound modification or augmentation in response to object recognition and/or sound detection associated with a particular user response, determined by machine learning). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Baughman et al into the teaching of Smith et al and Reinspach et al to improve user experience (e.g. Baughman et al, column 2, line 65-coolumn 3, line 15).
For claims 9 and 23, Smith et al and Reinspach et al do not further disclose the computing environment is augmented environment. Baughman et al teach the computing environment is augmented environment. (e.g. column 2, line 65-column 3, lines 15: One approach by which a user may change the context is through the application of sound modification or augmentation in response to object recognition and/or sound detection associated with a particular user response, determined by machine learning). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Baughman et al into the teaching of Smith et al and Reinspach et al to improve user experience (e.g. Baughman et al, column 2, line 65-coolumn 3, line 15).
Claims 12, 26, and 31 are rejected under 35 U.S.C. 103 as being unpatentable over Smith et al and Reinspach et al, as applied to claims 1, 4-5, 13, 15, 18-19, 27-30, and further in view of Maurer et al (US 2024/0176960).
For claims 12, 26 and 31, Smith et al and Reinspach et al do not further specify the first input and the second input are received synchronously. Maurer et al teach the first input and the second input are received synchronously (e.g. paragraph 150: … a recognized term uttered or otherwise input by a participant within a synchronous multimedia collaboration session. Thus, if, for example, a synchronous multimedia collaboration session is initiated … the ML model(s) 142 may be trained to recognize any of the frequently occurring terms “development,” “testing,” “scripts” or the like as particularly relevant contextually…). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Maurer et al into the teaching of Smith et al and Reinspach et al to improve user experience.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Smith et al and Reinspach et al, as applied to claims 1, 4-5, 13, 15, 18-19, 27-30, and further in view of Jenny et al (US 2016/0037068).
For claim 14, Smith et al and Reinspach et al do not further disclose generating, by the content creation system, a signal for displaying a graphical interface to the first user or the second user; receiving, by the content creation system, a selection command from the first user or the second user; and providing, by the content creation system, a user created element in the computing environment based on the selection command, wherein the graphical interface includes an adjustable timeline, wherein the selection command selects a time period on the adjustable timeline, and wherein the user created element is selected by the content creation system based on the time period. Jenny et al teach generating, by the content creation system, a signal for displaying a graphical interface to the first user or the second user; receiving, by the content creation system, a selection command from the first user or the second user; and providing, by the content creation system, a user created element in the computing environment based on the selection command, wherein the graphical interface includes an adjustable timeline, wherein the selection command selects a time period on the adjustable timeline, and wherein the user created element is selected by the content creation system based on the time period (e.g. figure 3, paragraph 71: user input of positioning second adjustable element 318 along timeline 314. The positioning of second adjustable element 318 may correspond to a selection of a reference time instance. By way of non-limiting example, positioning of second adjustable element 318). It would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teaching of Jenny et al into the teaching of Smith et al and Reinspach et al to improve user experience.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAQUAN ZHAO whose telephone number is (571)270-1119. The examiner can normally be reached M-Thur: 7:00 am-5:00 pm.
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Email: daquan.zhao1@uspto.gov.
Phone: (571)270-1119
/DAQUAN ZHAO/Primary Examiner, Art Unit 2484
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